Pseudobulbar Affect Correlates with Mood Symptoms and Low Quality of Life in Patients with Parkinson's Disease: A Comprehensive Cross-Sectional Study
Bibliographic record
Abstract
P seudobulbar affect (PBA) is a condition characterized by uncontrollable episodes of crying and laughing. [1]t is linked to Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, brain tumors, stroke, and dementia.Often referred to by terms like emotional lability and pathological laughing and crying, PBA significantly affects social interactions and quality of life, potentially leading to secondary mental health issues like anxiety and depression. [1,2]PBA is frequently mistaken for mood disorders, including depression and bipolar disorder, but it can be distinguished by its characteristic sudden, exaggerated emotional reactions that patients are unable to control, often occurring in situations that seem inappropriate for such responses. [2,3]jectives: Despite being recognized for a long time as a characteristic of Parkinson's disease (PD), pseudobulbar affect (PBA) is still a symptom that is underdiagnosed and undertreated.This study aimed to assess the association between PBA and various mood disturbances, as well as the impact on quality of life in PD patients.Methods: Sixty-eight patients with PD were enrolled in this study.Their demographic and clinical features, including age, gender, education, smoking, lateralization and duration of the disease, and comorbidity, were recorded.The scores on the Unified Parkinson's Disease Rating Scale (UPDRS), Hoehn-Yahr Scale, The Mental Component Summary (MCS-12), the Physical Component Summary (PCS-12), The Montreal Cognitive Assessment, and Beck Depression Inventory were evaluated.The Center for Neurologic Study-Lability Scale (CNS-LS) was used to explore PBA.Results: There were 12 patients (17%) with CNS-LS scores of 13, and 4 patients (5%) with CNS-LS scores of 4.BDI scores demonstrated a strong positive correlation with CNS-LS scores (Spearman correlation coefficient=0.64,p<0.001), and MCS-12 scores showed a significant negative correlation with CNS-LS scores (Spearman correlation coefficient=-0.70,p<0.001).The multivariate linear regression analysis showed that lower MCS-12 scores are related to higher CNS-LS scores, and higher BDI scores are also linked to higher CNS-LS scores. Conclusion:Our results indicate that elevated depressive symptoms correspond with increased CNS-LS scores, while a lower quality of mental health is also linked to higher CNS-LS scores.These findings highlight the influence of mood and mental health status on PDA among patients with PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".